Cleanup real labels in validate.py, no need to track original, will do that via exteran script

validate.py

@@ -218,22 +218,17 @@ def validate(args):
                         loss=losses, top1=top1, top5=top5))
 
     if real_labels is not None:
-        real_top1 = real_labels.get_accuracy(k=1)
-        real_top5 = real_labels.get_accuracy(k=5)
-        results = OrderedDict(
-            top1=round(real_top1, 4), top1_err=round(100 - real_top1, 4),
-            top5=round(real_top5, 4), top5_err=round(100 - real_top5, 4),
-            top1_original=round(top1.avg, 4),
-            top5_original=round(top5.avg, 4))
+        # real labels mode replaces topk values at the end
+        top1a, top5a = real_labels.get_accuracy(k=1), real_labels.get_accuracy(k=5)
     else:
-        results = OrderedDict(
-            top1=round(top1.avg, 4), top1_err=round(100 - top1.avg, 4),
-            top5=round(top5.avg, 4), top5_err=round(100 - top5.avg, 4))
-    results.update(OrderedDict(
+        top1a, top5a = top1.avg, top5.avg
+    results = OrderedDict(
+        top1=round(top1a, 4), top1_err=round(100 - top1a, 4),
+        top5=round(top5a, 4), top5_err=round(100 - top5a, 4),
         param_count=round(param_count / 1e6, 2),
         img_size=data_config['input_size'][-1],
         cropt_pct=crop_pct,
-        interpolation=data_config['interpolation']))
+        interpolation=data_config['interpolation'])
 
     _logger.info(' * Acc@1 {:.3f} ({:.3f}) Acc@5 {:.3f} ({:.3f})'.format(
        results['top1'], results['top1_err'], results['top5'], results['top5_err']))